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Duration 28 hours
Course Outline
Introduction to Multi-Robot Systems
- Exploration of multi-robot coordination and control architectures.
- Industry, research, and autonomous system applications.
- Analysis of centralized versus decentralized system approaches.
Foundations of Swarm Intelligence
- Core principles of collective intelligence and self-organization.
- Bio-inspired models: ants, bees, and bird flocks.
- Emergent behaviors and system robustness in swarms.
Communication and Coordination
- Inter-robot communication models and protocol design.
- Consensus algorithms and distributed agreement mechanisms.
- Strategies for task allocation and resource sharing.
Control and Formation Strategies
- Leader-follower, behavior-based, and virtual structure control methods.
- Algorithms for flocking, coverage, and pursuit–evasion.
- Maintaining formation integrity under noisy communication conditions.
Swarm Optimization Algorithms
- Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO).
- Applications in path planning and dynamic task assignment.
- Hybrid methods integrating machine learning with swarm heuristics.
Simulation and Implementation
- Constructing multi-robot simulations within ROS 2 and Gazebo.
- Implementing swarm behaviors using Python or C++.
- Debugging processes and analysis of emergent dynamics.
Advanced Topics in Swarm Robotics
- Scalability, fault tolerance, and communication resilience.
- Integration of machine learning for adaptive coordination.
- Human-swarm interaction and supervisory control mechanisms.
Practical Project: Designing and Simulating a Swarm Coordination System
- Defining objectives and constraints for multi-robot missions.
- Implementation of swarm coordination algorithms.
- Evaluation of performance metrics and system robustness.
Conclusion and Future Directions
Requirements
- A solid grasp of fundamental robotics concepts.
- Proficiency in Python programming and the ROS ecosystem.
- Knowledge of algorithms related to motion planning and control systems.
Target Audience
- Robotics researchers specializing in distributed and cooperative systems.
- System architects developing large-scale multi-agent robotic solutions.
- Senior developers focused on autonomous coordination and swarm algorithms.
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.